ArticleSensors (Basel, Switzerland)2021
Self-Relative Evaluation Framework for EEG-Based Biometric Systems.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A PRISMA-based systematic review on advances in identity recognition and authentication using human biometric signals (2018-2023).Biomedical engineering online · 2026Pooled it
- Towards Cognitive Authentication for Smart Healthcare Applications.Sensors (Basel, Switzerland) · 2022Article
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Authors and funding
2 authors.
Funding
Abstract
In recent years, electroencephalogram (EEG) signals have been used as a biometric modality, and EEG-based biometric systems have received increasing attention. However, due to the sensitive nature of EEG signals, the extraction of identity information through processing techniques may lead to some loss in the extracted identity information. This may impact the distinctiveness between subjects in the system. In this context, we propose a new self-relative evaluation framework for EEG-based biometric systems. The proposed framework aims at selecting a more accurate identity information when the biometric system is open to the enrollment of novel subjects. The experiments were conducted on publicly available EEG datasets collected from 108 subjects in a resting state with closed eyes. The results show that the openness condition is useful for selecting more accurate identity information.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.